300 results about "Heat transfer model" patented technology

The invention relates to the technical field of industrial control, and discloses a dry-wet combined cooling tower operation state prediction and diagnosis system comprising a load prediction module used for obtaining production plan data and environment information, constructing a basic heat load prediction model, and outputting a total prediction heat load; the thermal modeling module is used for establishing a heat transfer model and an energy consumption model, the heat transfer model outputs cooling amounts in different operation modes, and the energy consumption model outputs total predicted power; the dry-wet decision module is used for constructing a multi-objective optimization function and solving the multi-objective optimization function to obtain a dry-wet switching strategy; and the control execution module is used for executing the dry-wet switching strategy. According to the method, the basic thermal load prediction model is established, so that the prediction precision of the thermal load is improved, and differentiated cooling strategies are provided for different production stages; on the basis of real-time load requirements and environmental conditions, a dry mode or a wet mode is intelligently selected for operation, and a multi-objective optimization function is constructed, so that the balance between cooling requirement meeting and system energy consumption minimization is realized.

The invention relates to a multi-cell control method for hydrogen production alkaline electrolytic cells based on nonlinear model predictive control, which belongs to the technical field of hydrogen production and comprises the following steps of: performing data acquisition on key positions of a hydrogen production alkaline electrolytic cell system in real time; based on the dynamically determined priority of each electrolytic cell, dynamic load distribution of each electrolytic cell is carried out, and a multi-dimensional cooperative regulation strategy is implemented to obtain a hydrogen yield target value of each electrolytic cell; constructing a nonlinear model comprising an electrolytic reaction model, a heat transfer model and an inter-tank coupling model, and performing parameter identification and verification; and designing a nonlinear model predictive control algorithm, performing discretization processing on the nonlinear model, introducing Kalman filtering to process the uncertainty of the model, taking a corresponding hydrogen yield target value reached by each electrolytic cell on the premise of meeting the constraint as a final control target, constructing an optimized target function, and performing solving to obtain an optimal control scheme. Compared with the prior art, the control precision and the system stability can be effectively improved.

The invention provides a lithium ion battery core temperature prediction method based on a finite element model, and the method comprises the following steps: 1, designing an electrochemical test experiment, and constructing a one-dimensional electrochemical model containing a lithium ion battery electrochemical heat production mechanism; 2, designing a lithium ion battery temperature test experiment, obtaining electrochemical parameters, heat transfer characteristic parameters, internal thermophysical parameters and environmental parameters of the battery under different working conditions, and obtaining a temperature change curve of the center position and the surface of the battery; and step 3, based on the heat balance equation, establishing a three-dimensional heat transfer model having the same geometric characteristics as the battery used in the experiment. According to the experimental result in the step 2, the three-dimensional heat transfer model is subjected to non-uniform region division, each region corresponds to one one-dimensional electrochemical model, and the heat production rate per unit volume is calculated by the one-dimensional electrochemical model in the step 1; introducing the heat production rate of each area into a three-dimensional heat transfer model to calculate the temperature distribution of the battery, and designing an experiment to correct a one-dimensional electrochemical model; 4, modifying the operation conditions and heat dissipation conditions of the battery, and calculating and analyzing the temperature difference delta T between the center position and the surface position of the battery under different operation conditions and heat dissipation conditions by using the three-dimensional heat transfer model in the step 3; and 5, measuring the surface temperature of the battery, and calculating the temperature of the center of the battery according to the working condition of the battery in the step 4 and the delta T corresponding to the environment temperature, thereby realizing monitoring of the temperature of the center position of the battery. According to the method, a high-precision algorithm model is constructed and verified by utilizing data accumulated in an earlier-stage experiment, the central point temperature which is difficult to directly measure in the battery is predicted only through real-time and easily-acquired battery surface temperature information, operation condition parameters and heat dissipation conditions, key thermal state information is provided for a battery management system, and the battery management efficiency is improved. The method is used for real-time safety monitoring and thermal management optimization.

The invention discloses a rock-soil temperature field rapid solving method suitable for a ground source heat pump system, and the method comprises the steps: firstly building a three-dimensional unsteady-state heat transfer model in consideration of a buried pipe coaxial structure, a porous arrangement form and the characteristics of a multilayer heterogeneous soil body in the ground source heat pump system; then simulating a thermal response process by using the model, constructing a multi-domain coupled thermal conduction augmentation matrix, performing POD on the matrix, extracting a dominant mode function of a temperature field, and constructing a low-dimensional POD-based mode space; and finally, constructing a POD-Galerkin low-order model, simulating a buried pipe group soil temperature field, performing inversion of a heat source function, and outputting stratum thermophysical parameters. According to the method, the calculation efficiency and the simulation precision of the porous coupling and long-period unsteady state heat transfer process are remarkably improved, the problem that traditional finite element and finite difference methods are high in time consumption in porous strong coupling modeling is solved, and rapid prediction of the soil temperature and robust recognition of the heat source function under a complex stratum and a heat exchange structure can be achieved.

The invention relates to the technical field of infrared thermal imaging, in particular to a human body analysis method and system based on an infrared thermal image. The method comprises the following steps: acquiring an infrared thermal image sequence of a limb to be detected in a thermal relaxation process; segmenting the image sequence, constructing a topological center line of an effective contour, and defining a heat flow reference direction based on the geometric width change of a cross section along the center line; a temperature gradient vector field is calculated, and an area with the gradient direction and the heat flow reference direction in reverse distribution and containing a closed isotherm is screened out to serve as a thermal topology abnormal area; establishing a biological heat transfer model taking the surface temperature as a boundary condition, performing inverse solution on the thermal topology abnormal region, and performing inverse calculation on a heat source parameter corresponding to the subcutaneous depth; and when the heat source parameter exceeds a threshold value, generating a damage early warning. According to the method, by quantifying metabolic heat abnormality caused by inflammation in tissues, accurate positioning and quantitative evaluation of deep injury of limbs are realized, and the accuracy of human injury detection is remarkably improved.

The invention provides a high-strength aluminum alloy selective laser melting forming thermal stress prediction method based on deep learning. The method comprises the steps of 1, finite element model establishment and simulation, wherein a heat transfer model and a thermal coupling model are established; an SLM process is used as a simulation object, a Gaussian model is adopted to define a laser heat source, and thermal stress distribution under different process parameters and different sample sizes is simulated; wherein the process parameters comprise laser power, scanning speed and hatch spacing; step 2, data processing and deep learning model training; comprising the steps of data preprocessing, neural network model architecture determination, adversarial network part generation and model configuration and training. 3, evaluating and optimizing the model; and 4, thermal stress prediction and process optimization. By learning a complex mode in finite element simulation data through a deep learning model, efficient and accurate thermal stress prediction is achieved, and the problems that traditional finite element analysis is complex in calculation and large in resource consumption are solved.

The invention relates to the technical field of power system demand side management and optimization operation, and discloses an electric heating load master-slave game collaborative optimization method based on AP clustering and adjustable potential modeling, which comprises the following steps: establishing a directly-heated electric heating indoor heat transfer model to analyze a single user to obtain load characteristics of heating users; a decentralized electric heating load refined aggregation model is constructed, and decentralized heating users are divided into different clusters; an adjustable potential quantification model is constructed, and the adjustable electric quantity and the adjustable potential of each cluster are obtained; and a heating load group optimization operation model based on the master-slave game is constructed, power grid purchase and sale electricity price information, distributed power supply cost information, adjustable electric quantity and adjustable potential are input, and a power utilization behavior adjustment strategy is obtained. According to the method, through refined house type clustering, master-slave game framework design and an improved solution algorithm, precise mining and optimized operation of the heating load group regulation potential are realized, the peak regulation pressure of a power grid is effectively reduced, and the comfort of a user is considered.

The invention relates to the technical field of intelligent construction of road engineering, and discloses an expressway asphalt pavement construction data analysis and processing system, the system performs digital modeling on an asphalt mixture and anchors the asphalt mixture to a pavement three-dimensional coordinate by creating a material state vector including a static attribute, a dynamic state and a process resume, and the system adopts a heat transfer model to construct an asphalt pavement construction data analysis and processing system. And the predicted temperature of the target vector at the future interception moment of the road roller is updated in real time and forwards simulated. Meanwhile, the system calculates a dynamic compactability window according to the compaction history and the material type, compares the predicted temperature with the window, generates a feedforward control instruction of a standard, priority or waiting operation, converts the feedforward control instruction into visual guidance, and issues the visual guidance to the vehicle-mounted terminal, so that prospective control is realized. According to the invention, the conversion of construction control from passive lag to active feedforward is realized, the fineness of the compaction process is improved, and a reliable digital quality tracing mechanism is established.

The invention belongs to the technical field of computer aided design, and provides a C / C composite material thermochemical response and pore scale structure evolution prediction method, which comprises the following steps: constructing a geometric model of the pore scale of a rocket engine jet pipe; establishing a fluid flow model in a D2Q9 form; establishing a multi-component mass transport model in a D2Q5 form; establishing a heat transfer model in a D2Q5 form; establishing a heterogeneous chemical reaction model of the fluid-solid boundary; establishing an updating model of the composite material based on a volume pixel method; and based on a geometric model, a fluid flow model, a multi-component mass transport model, a heat transfer model, a heterogeneous chemical reaction model and an update model, predicting the thermochemical response and pore scale structure evolution of the C / C composite material in the rocket engine nozzle. The method is provided for studying the ablation process of the C / C composite material, and theoretical basis and guidance direction are provided for thermal performance study and fine design of the spray pipe.

The invention discloses a flexible sunlight greenhouse temperature control method, system and device and a storage medium, and relates to the technical field of greenhouse environment, the method comprises the following steps: calling a heat transfer model to carry out temperature field simulation calculation according to greenhouse internal thermal field distribution data to obtain a first predicted temperature value; calling a greenhouse temperature prediction model to perform time sequence analysis on the external environment temperature historical time sequence data to obtain a second predicted temperature value; performing data fusion according to the first predicted temperature value and the second predicted temperature value to obtain a comprehensive predicted temperature value; and according to a deviation value between the comprehensive prediction temperature value and a preset greenhouse air temperature target value, adjusting operation parameters of the greenhouse equipment. By simulating thermal field distribution in a greenhouse and processing time sequence data of an external environment, a deterministic rule and random fluctuation are covered, a deviation value with a target value is calculated according to an obtained comprehensive prediction value, and equipment is dynamically adjusted based on prediction deviation, so that ineffective energy consumption and equipment loss are reduced.

The invention discloses a flow resistance and heat transfer simulation analysis method for a thermal management refrigerant side integrated module, and relates to the technical field of computer simulation. The method mainly comprises the following steps of: dividing a computational domain model into a solid domain, a fluid domain comprising a plurality of single-phase flow channel sub-domains and a flow channel section which is in a gas-liquid two-phase state and exchanges latent heat along with phase change in combination with the need of an actual analysis working condition; performing polynomial fitting on various parameters by fixing the inlet pressure value of each single-phase flow channel sub-domain; loading the fitted physical property function to the corresponding runner sub-domain, and setting a constant material attribute for the solid domain runner plate; a conjugate heat transfer model is started on an interface of a fluid domain and a solid domain, and interface heat flux density conservation and temperature continuity simulation is carried out; setting boundary conditions; and executing conjugate heat transfer simulation calculation until convergence calculation is completed. According to the method, the simulation precision is improved through fusion of three core technologies of dynamic change physical property fitting, solid-liquid conjugate heat transfer coupling and two-phase flow latent heat equivalent modeling.

The present invention relates to the technical field of electrodeposition, and relates to a simulation method for flow field distribution and deposition morphology in ultrafast laser-assisted electrochemical deposition. The steps of the method comprise: constructing, in multiphysics simulation software, a two-dimensional axisymmetric multiphysics coupled field model for heat transfer, solid and fluid heat transfer, tertiary current distribution, and laminar flow; constructing a geometric model of a deposition cell and a substrate, and setting laser properties, material physical parameters, and electrodeposition properties in the multiphysics simulation software; constructing an ultrafast laser heat transfer model on the basis of a two-temperature equation; setting initial and boundary conditions of the ultrafast laser heat transfer model, and constructing an electrodeposition field; coupling the ultrafast laser heat transfer model with the electrodeposition field to construct an ultrafast laser-assisted electrochemical deposition model; delineating a grid; and performing calculation and analysis. In the present invention, ultrafast laser is incorporated to perform multiphysics coupling of a thermal field, a flow field, an electric field, etc., and a two-temperature equation and tertiary current distribution are incorporated to the model, thereby achieving the accuracy and comprehensiveness of prediction models.

The invention discloses an automatic shell-making wire environment simulation system. The system comprises an environmental parameter testing unit, a heat and mass transfer model establishing unit and an optimization processing unit. The environmental parameter testing unit is used for testing environmental parameters influencing the drying process of the shell-making drying cabin through testing equipment, evaluating the uniformity of airflow in the drying cabin and the change condition of the environmental parameters, and sending testing and evaluating results to the heat and mass transfer model establishing unit; the environmental parameters at least comprise wind speed. And the heat and mass transfer model building unit is used for building a shell drying heat transfer model and a shell drying mass transfer model, evaluating the shell drying heat transfer model and the shell drying mass transfer model based on the model expression indexes after building is completed, and analyzing the influence of the environmental parameters on shell heat transfer and mass transfer based on the information transmitted by the environmental parameter testing unit. And the optimization processing unit is used for introducing the influence of load, airflow in the drying cabin and air into the established shell drying heat transfer model and shell drying mass transfer model for simulation and optimization.

This invention provides a method for modeling the starting performance of a marine gas turbine. First, a gas turbine aero-thermodynamic performance calculation model is established using C++, and a heat transfer model, temperature sensor model, and control law model for the gas turbine's high-temperature components are established using the M language. Then, based on test data from the gas turbine startup process, the method analyzes how the pressure ratio and efficiency of typical gas turbine components change with the physical speed of the gas generator during startup. The corresponding low-speed characteristics of the gas turbine's rotating components are generated and corrected, enabling high-precision, real-time simulation of the gas turbine's starting performance. This method considers the heat exchange between the high-temperature fuel gas and the ambient atmosphere and the gas turbine itself, improving the accuracy of the gas turbine startup performance simulation. The method can provide a simulation testing tool for the design and optimization of gas turbine startup control laws.

The invention discloses an optimization method of a ground source heat pump, electronic equipment and a program product, and the method comprises the steps: collecting the operation data and environment data of a ground source heat pump system in real time through an edge computing gateway deployed on site; constructing a multi-objective optimization model of the ground source heat pump system on the cloud server; solving the optimization model by adopting a self-adaptive multi-target genetic algorithm, and outputting a Pareto optimal solution set; selecting a final execution scheme from the Pareto optimal solution set according to a preset decision preference weight, generating a control instruction, and issuing the control instruction to the field executor through the edge computing gateway; the soil temperature field evolution is predicted through the buried pipe heat transfer model, and a prediction result is fed back to the optimization model and used for correcting the soil heat balance objective function, and long-term dynamic optimization is achieved. According to the method, collaborative optimization of economy, environmental protection and sustainability can be realized by constructing the multi-objective optimization model fusing the operation cost, the soil heat balance and the carbon emission.

The invention discloses a calculation method and a calculation device for a film state boiling starting point of a surface with dirt, and belongs to the field of nuclear power. The calculation method for the membrane state boiling starting point of the surface with the dirt comprises the following steps: establishing a fuel rod cladding surface heat exchange model with the dirt according to a fuel rod cladding model with the dirt and thermal parameters, and calculating to obtain a heat conductivity coefficient and permeability of a dirt area; calculating the gas film thickness at the beginning of film boiling; according to the pressure balance and energy conservation equation, the heat flux corresponding to the minimum gas film thickness value is obtained through calculation and serves as the initial heat flux of film boiling. The method can accurately calculate the initial heat flux density of membrane boiling under the influence of dirt, and improves the precision of systematically analyzing the influence of dirt on the thermal hydraulic performance of a reactor.

The present invention discloses a multi-objective thermal-fluid topological design optimization method for the cooling element of a precision gear grinding machine tool, comprising the following steps: Step 1: Define the design domain: Expand the cooling element into a plane, define a two-dimensional design domain representing the cooling element's geometric structure, and discretize it using the finite element method; Step 2: Numerical modeling: Model the cooling element as a porous medium; Under the conditions of laminar incompressible flow, the fluid dynamics are governed by the dimensionless forms of the continuity equation and the momentum equation; The fluid-solid coupled heat transfer model is governed by the dimensionless energy conservation equation; Step 3: Construct an objective function: The optimization objective is defined as a weighted function of heat transfer and fluid dissipated power, and a fluid-solid heat transfer topological optimization model is constructed; Step 4: Solve the objective function; Step 5: Restore the shape and structure of the cooling element. The present invention also discloses a precision gear grinding machine tool and a cooling element.

The invention provides a loudspeaker voice coil temperature detection method and device, electronic equipment and a storage medium, and relates to the technical field of signal processing. The loudspeaker voice coil temperature detection method comprises the following steps: acquiring the current input power of a voice coil of a loudspeaker; inputting the current input power into a voice coil temperature detection model used for representing the mapping relation between the input power of the voice coil of the loudspeaker and the temperature of the voice coil of the loudspeaker, and obtaining the target temperature, output by the voice coil temperature detection model, of the voice coil of the loudspeaker; wherein the voice coil temperature detection model is a loudspeaker heat transfer second-order model established based on target heat parameters; the target thermal parameters at least comprise a first target thermal parameter between a voice coil of the loudspeaker and a magnetic circuit of the loudspeaker, a second target thermal parameter between the magnetic circuit of the loudspeaker and air, and a third target thermal parameter between the voice coil of the loudspeaker and air convection. According to the technical scheme provided by the invention, the detection of the voice coil temperature of the loudspeaker is realized, and the precision of voice coil temperature detection is improved.

The invention discloses an explanation method for damage threshold improvement of a fused quartz material in a femtosecond laser processing / welding process. By establishing a fused quartz electron-lattice heat transfer model under femtosecond laser irradiation, a dissociation model of environment molecules and interstitial molecules under the action of femtosecond laser and a defect-containing fused quartz molecule dynamic reaction model based on a ReaxFF reaction force field, atomic structure changes in a system before and after a reaction are analyzed; and finally, obtaining a chemical reaction mechanism of the fused quartz containing the defects under the action of the femtosecond laser, and explaining the phenomenon that the damage threshold of the fused quartz is increased after the fused quartz is irradiated by the low-flux femtosecond laser. According to the method, the research in the current fused quartz femtosecond laser processing / welding process is perfected, and meanwhile, the theoretical blank that the damage threshold lifting mechanism is not clear in the fused quartz glass femtosecond laser processing / welding process is filled up.

The invention provides a mid-deep layer coaxial buried pipe group optimization design method which specifically comprises the following steps: S1, according to the structural design of mid-deep layer coaxial buried pipes, establishing a three-dimensional heat transfer model of a mid-deep layer buried pipe heat exchanger based on a bicontinuum finite element method; s2, setting model parameters; s3, inlet temperature, heat extraction power and buried pipe spacing parameters are set, and middle-deep layer coaxial buried pipe group heat extraction amount, adjacent rock-soil temperature or outlet temperature are output; and S4, selecting inlet temperature, heat extraction power and buried pipe spacing parameters as an optimal design scheme of the middle-deep layer coaxial buried pipe group according to the output heat extraction amount of the middle-deep layer coaxial buried pipe group, the adjacent rock-soil temperature or the outlet temperature. According to the method, the medium-deep buried pipe group three-dimensional heat transfer model is established, the influence degree of different pipe group design parameters on the long-term operation heat extraction performance of the system is quantitatively evaluated, and a theoretical basis is provided for actual engineering.

The invention relates to the technical field of solid oxide fuel cells, and discloses a construction method of a solid oxide fuel cell multi-physical field bidirectional strong coupling simulation model and a computer program product. The method comprises the following steps: respectively constructing an electrochemical model, a positive / negative electrode fluid flow model and a heat transfer model of the solid oxide fuel cell based on an established geometric structure model; solving equations of the physical fields in all the models are combined to form a full coupling matrix, and iterative solving is carried out according to a set initial value; and judging whether the constructed model is converged or not according to an iterative solution result. According to the model constructed by the method, the mutual influence among electrochemistry, flow and heat transfer processes is fully considered, and synchronous solving is performed through a unified matrix system, so that real-time interaction and collaborative updating among multiple physical fields are realized, and the convergence efficiency and numerical stability of a nonlinear coupling problem are remarkably improved; through inspection, the deviation between a simulation result and actually measured data is less than 8%, and the method has high engineering practical value.

The invention discloses a battery extreme high temperature thermal runaway temperature prediction method and system, a medium and electronic equipment. The method comprises the following steps: setting a battery thermal runaway equation set and a battery heat transfer equation set; establishing a cell three-dimensional thermal runaway simulation model with electrochemical reaction and a soft package battery three-dimensional heat transfer model; performing a simulation experiment based on a high-temperature impact test condition, setting different heat source distances for the three-dimensional heat transfer model of the soft package battery, and performing heat transfer calculation based on a battery heat transfer equation set to obtain a heat transfer temperature; for the three-dimensional thermal runaway thermal runaway simulation model of the battery cell, adjusting different SOC battery energy, loading heat transfer temperature at the same time, obtaining internal thermal runaway heat production of the battery cell through a battery thermal runaway equation set, obtaining high-temperature impact thermal runaway simulation data, and training a temperature prediction model; and performing real-time temperature prediction and thermal runaway early warning by applying the trained temperature prediction model. The thermal runaway early warning timeliness and reliability are remarkably improved.

The invention belongs to the technical field of ground source heat operation management, and particularly discloses an intelligent operation management system for geothermal energy in a severe cold area. The system comprises an acquired data verification module, a soil dynamic analysis module, a thermal imbalance risk prediction module and a control priority determination module. According to the method, geothermal operation data are collected and verified in real time, key indexes such as heating power, soil accumulated heat taking capacity and heat recovery rate are calculated, meteorological prediction data are combined to drive a soil heat transfer model to conduct prospective simulation, and a heat imbalance risk index is output. And the control priority of the heat supply quality and the soil heat imbalance is dynamically determined and output based on the risk index and the change trend thereof, so that the heat recovery capability of the soil is effectively maintained while the heat supply requirement is met, and meanwhile, the priority management direction between the heat supply quality guarantee and the soil heat imbalance prevention and control is defined; and therefore, effective balance is realized between maintaining the heating demand of the user and protecting the sustainability of terrestrial heat.

The invention discloses an external clamping type flow sensor medium temperature calculation method, and relates to the technical field of testing and metering, and the method comprises the steps: obtaining the outer wall temperature measurement values of two sensors through a temperature collection device; by means of double-temperature-probe averaging treatment, accidental errors of single-point measurement are effectively reduced, three heat transfer mechanisms of heat transfer, solid heat conduction and convection-radiation combined heat dissipation are constructed, a fluid dynamic criterion is introduced to accurately calculate a convection heat transfer coefficient, quantitative heat transfer models outside and inside the tube are constructed, and the heat transfer efficiency is improved. By introducing an empirical formula dynamically coupled with the environment wind speed and a fluid mechanics criterion correlation formula based on the Reynolds number criterion, scene self-adaption accurate calculation of the key heat exchange coefficient is achieved, iterative correction of fluid physical property parameters is combined, and through iterative calculation and real-time correction of the physical property parameters, the real-time correction of the fluid physical property parameters is achieved. A three-layer progressive error correction system of dynamic time correction, scene database correction and multi-dimensional anti-interference correction is established, and high precision and high reliability of temperature calculation are achieved.

The invention relates to the technical field of automatic control, and discloses a multi-parameter collaborative intelligent temperature regulation control system for a pot-type calcining furnace, and the system comprises a collaborative detection and cognition module which is used for calculating a dynamic thermal response spectrum according to operation data, and recognizing process stage information; the online modeling and state estimation module is used for updating an equivalent heat transfer model online by using the dynamic thermal response spectrum and estimating the core temperature of the material; and the collaborative prediction and decision module is used for calculating a basic control law by solving an optimization problem according to the process stage information, the updated model and the core temperature estimation value. According to the invention, through a collaborative closed-loop adaptive control architecture of cognition, modeling and decision-making, the process stage can be autonomously identified, the accurate control of the core temperature can be realized, and the temperature control precision of the whole process, the product quality consistency and the system adaptive capability are obviously improved.

The invention discloses an automatic control system for drying waste heat recovery. The automatic control system comprises a heat energy utilization rate calculation module, a flow control module, an airflow analysis module and an adjusting module. The heat energy utilization rate calculation module calculates the current heat energy utilization rate in combination with a preset heat transfer model to obtain the matching deviation of heat exchanger operation and dryer state; the flow control module extracts wind speed and pressure distribution data from the air duct system, analyzes the uniformity of airflow distribution by adopting an airflow simulation algorithm, and determines a deviation area and an adjustment amplitude of air volume adjustment; the airflow analysis module executes accurate adjustment through an automatic control module of an air volume adjusting valve according to the deviation area, the adjusted air speed and pressure data are obtained, and whether airflow distribution reaches a preset uniformity standard or not is judged; the adjusting module obtains flow and temperature monitoring data of the condensate water pipeline, analyzes linkage efficiency of condensate water management and waste heat recovery in combination with a heat recovery rate calculation formula of the waste heat recovery device, and determines optimization requirements.

The invention provides a simulation method and system for a solar ground source heat pump system, and relates to the technical field of solar ground source heat pump system simulation, and the method comprises the steps: firstly obtaining a soil initial temperature field, and calculating the soil temperature cumulative variation in a future time period through a one-dimensional radial simplified heat transfer model in combination with a predicted load; defining as a soil thermal imbalance risk index; according to comparison between the index and a preset threshold value, selecting an efficiency priority strategy with solar energy immediate utilization as priority or a heat balance priority strategy with soil temperature field adjustment as priority; linkage rules of all subsystems are determined according to a selected strategy, the net heat exchange amount of a geographical pipe heat exchanger and the net heat storage / release amount of a heat storage device are calculated by jointly solving a dynamic model, and then the soil temperature field and the state of the heat storage device are updated; and the simulation step length is iteratively propelled until the period is ended, and finally, the system energy efficiency coefficient, the soil heat balance degree and the time-varying curve of the key parameters are output.

The invention provides a solid-state heat pipe reactor core equivalent heat transfer calculation method and device and a storage medium, and the method comprises the steps: simplifying a basic heat transfer unit with a non-circular three-dimensional structure in a reactor core into a one-dimensional radial heat transfer model based on a volume conservation principle; constructing a three-dimensional heat transfer model of the basic heat transfer unit, and performing numerical simulation under a preset boundary condition to obtain first temperature field data serving as a reference; second temperature field data are calculated according to the one-dimensional radial heat transfer model and the original physical property parameters, the first temperature field data serve as a target, iterative correction is conducted on the original physical property parameters till the second temperature field data output by the one-dimensional radial heat transfer model and the first temperature field data meet a preset convergence criterion, and the original physical property parameters are obtained; therefore, the corrected equivalent physical property parameters are determined; and applying the corrected equivalent physical property parameters to a control equation of a full-reactor-core system-level transient analysis program, and obtaining the temperature field distribution of the full reactor core through numerical discretization and iterative solution.

The invention relates to the technical field of superconducting cables, in particular to a three-dimensional heat-flow decoupling modeling method and device for a three-phase three-axis high-temperature superconducting cable, and the method comprises the steps: constructing a simplified three-phase three-axis high-temperature superconducting cable geometric model; constructing a temperature distribution finite element model, wherein the temperature distribution finite element model comprises a decoupled fluid model and a heat transfer model; the dynamic temperature distribution of the three-phase three-axis high-temperature superconducting cable under the influence of transient factors is solved by using a temperature distribution finite element model, and the method comprises the following steps: 1) a steady state step: based on an initial boundary condition, completing basic solution of a cable temperature field and a liquid nitrogen flow velocity field under a steady state through coupling calculation of a fluid module and a heat transfer module; 2) a transient step: taking a result value of steady-state solution as an initial condition of transient solution, and finally outputting a temperature distribution simulation result through multi-step transient solution iteration and flow field and temperature field distribution.Compared with the prior art, the method has the advantages of high modeling precision, small calculation amount, fast convergence and the like.

The application discloses a kind of vacuum switch contact ablation intelligent evaluation method based on physical information fusion, belong to vacuum circuit breaker technical field.The method of the present application includes: according to the data set of vacuum switch breaking type obtained from vacuum arc experimental data, construct physical information enhanced support vector machine to predict breaking type of working condition;Vacuum arc simulation model is extracted from each working condition Contact surface energy flow density radial distribution data, and is fitted by Gaussian function;Based on the energy flow density radial distribution curve obtained by fitting, a vacuum arc simulation data set is constructed, and a physical information enhanced Gaussian process regression is constructed to predict the energy flow density of the working condition;Combining the heat transfer model to solve the radial distribution of contact surface temperature, further quantitatively evaluate the ablation degree of contact surface, and output the ablation degree level.The present application embeds the physical law of vacuum arc into machine learning model, realizes the breaking type prediction, energy flow density prediction and contact temperature rise calculation and ablation degree calculation and evaluation.